Batch-resolve a list of company names or scheme:value identifiers (lei/siren/br-cnpj/gb-coh/uen/sec/ofac/eu/un/uk/krs) to canonical WhiteIntel entity ids + confidence in ONE call. Enrich a whole supplier/counterparty list without one lookup per row. Up to 25 anon / 100 keyed.
| Name | Required | Description | Default |
|---|---|---|---|
| queries | Yes | Names or scheme:value identifiers. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, and the description adds valuable context: it returns entity ids + confidence, supports up to 25/100 queries, and mentions the result is canonical. Since the description aligns with annotations and adds rate/scale constraints, it goes beyond the structured data. However, it does not explain failure behavior or partial errors, which could be a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact yet information-dense: it opens with the core verb + resource, lists schemes, states the outcome (canonical ids + confidence), gives a motivating use case, and mentions rate limits. Every sentence serves a purpose, and it is appropriately front-loaded with the key capability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, schema covers it fully, annotations cover safety and idempotency), the description is sufficiently complete for an agent to invoke correctly. It covers purpose, schemes, batch nature, limits, and output. Missing details like error handling or response format are minor because there is no output schema, but the description gives the essential outcome ('canonical ids + confidence') to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'queries' with 100% description coverage ('Names or scheme:value identifiers'). The description adds the list of allowed schemes and batch semantics, which is helpful but not deeply beyond the schema. The baseline of 3 applies because schema coverage is high and the description adds minimal but useful additional meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description is highly specific: it states the tool batch-resolves company names or scheme:value identifiers to canonical entity IDs with confidence, and explicitly mentions supported schemes. It clearly distinguishes from siblings like lookup_by_identifier (likely single) and search_companies (likely search-oriented) by emphasizing batch and canonical resolution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear when-to-use context (enrich a whole supplier/counterparty list, avoid one lookup per row) and hints at limits (25 anon / 100 keyed). It does not explicitly name alternatives for when not to use it, but sibling context and the phrase 'ONE call' imply batch vs single use. Could be more explicit about fallback to single lookup tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes (search, lookup, get details, graph traversal, coverage maps, payment). Some overlap exists between lookup_company and lookup_by_identifier (both resolve identifiers, though one is UK-specific), and between get_entity vs get_company_details, but descriptions clarify distinctions. find_similar and semantic_search both find similar entities but different mechanisms.
Uses a mix of verb_noun and noun_phrases: buy_dossier, claim_dossier, check_offshore_exposure, find_similar, get_pricing, get_pulse, graph_neighbourhood, list_asset_coverage, lookup_by_identifier, search_entities, trace_ownership_path. While most use underscores and verbs like get/lookup/search/list, there are inconsistencies like 'graph_neighbourhood' (noun start) vs 'trace_ownership_path' (verb start). Overall readable but not perfectly consistent.
23 tools is at the high end but justifiable for a comprehensive intelligence server covering search, lookup, graph, coverage, payments, and entity details. 'buy_dossier' is considered one of the tools and adds bulk but not excessive. It is appropriate for the scope.
Covers a wide range: search (search_entities, search_companies, semantic_search), identifier lookup (lookup_by_identifier, lookup_company), entity details (get_entity, get_company_details, get_financials), graph (graph_neighbourhood, graph_path, trace_ownership_path), coverage maps (list_jurisdictions, list_asset_coverage), sanctions (get_sanctions, check_offshore_exposure), plus payment flow (get_pricing, buy_dossier, claim_dossier, get_payment_link). Missing perhaps a 'get_relationships' separate tool but get_entity includes direct relationships. Also no explicit 'list_entities' but search covers it. Minor gaps like no bulk operations besides resolve.
